Chapter 3 Find and Know Your Data

In the early stages of a visualization project, we often ask these two important and related questions: Where can I find data? and What do I really know about it? If you skip over these questions and leap too quickly into constructing charts and maps, you run the risk of creating meaningless, or perhaps worse, misleading visualizations. This chapter breaks down both of these broad questions, and provides concrete strategies to guide your search, understand debates about public and private data, navigate a growing number of open data repositories, source your data origins, and recognize bad data. Once you’ve found some files, we also ways to reflect on what you really know about your data. Information does not magically appear out of thin air. Instead, people collect and publish data, with explicit or implicit purposes, within the social contexts and power structures of their times. As data visualization advocates, we strongly favor evidence-based reasoning over less-informed alternatives. But we caution against embracing so-called data objectivity, since numbers and other forms of data are not neutral. Therefore, when working with data, pause to inquire more deeply about Whose stories are told? and Whose perspectives remain unspoken? Only by asking these types of questions, according to Data Feminism authors Catherine D’Ignazio and Lauren Klein, will we “start to see how privilege is baked into our data practices and our data products.”1

  1. Catherine D’Ignazio and Lauren F. Klein, Data Feminism (MIT Press, 2020),↩︎